spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. in this case, gis and geostatistics methods can be useful tools. spatiality of groundwater quality parameters, in relation with various land uses, can be very extremely. therefore water samples from 52 wells in the kurdan area were analyzed in this s...

accurate analysis and interpolation of heavy metals, especially arsenic concentrationin ground watercan play a significant role in planning and continuous monitoring of water resources. the analysis may also prevent human health issues.the purpose of this paper was to evaluate newly published sugeno type fuzzy inference system as an interpolation method for estimating the amount of arsenic in k...

Coseismic displacements play a significant role in characterizing earthquake causative faults and understanding earthquake dynamics. They are typically measured from InSAR using preand post-earthquake images. The displacement map produced by InSAR may contain missing coseismic values due to the decorrelation of ASAR images. This study focused on interpolating missing values in the coseismic dis...

In this paper we present a new publicly available high-resolution daily precipitation gridded dataset developed for peninsular Spain and the Balearic islands using 2756 quality-controlled stations (this dataset is referred to as Spain02). The grid has a regular 0.2 (aprox. 20km) horizontal resolution and spans the period from 1950 to 2003. Different interpolation methods were tested using a cro...

The groundwater quality research is one of the important and its pollution control was included insome research literatures. Ground water quality has spatial and temporal variation so classical statisticscould not account these variations at the regional scale researches. This study usedgeo-statisticalmethodsto optimize an interpolation method in order to estimate the spatial distribution of pH...

Knowing the piezometric levels evolution of an aquifer is essential for planning use water resources in cities central México, such as San Luis Potosí, whose population depends almost entirely on groundwater. Applying geostatistical methods from georeferenced data can reliably provide information spatial variability valley piezometry. The objective this study to evaluate static Potosí Valley, t...

Prediction of soil organic carbon (SOC) at unsampled locations is central to statistical modeling of regional SOC stocks. This is often accomplished by applying geostatistical techniques to plot inventory data. However, in many cases inventory data is sparsely sampled (<0.1 plots/km) relative to the region of interest, and it is unknown if geostatistics provides any advantage. Our objective was...